Cents-per-point (cpp) valuations across major loyalty programs from four publications. Floor/ceiling rules for deciding if a redemption is good or exceptional.
SkillScore88Maintained
Automatic
◆Personal Assistant pack
Last verified 8/16/2026
What it changes
Passed 22 of 25 test cases with the skill, and 16 of 25 without it.
Without skill64%
With skill88%
Checks it passed that the model alone missed
Flags the redemption as a sub-threshold overlay exception
Explains that partner transfers often beat this 1.0 cpp default rate
Instructs re-fetching source data from URLs in metadata to refresh rates
and 6 more in the full report
6 fixed16 passed either way3 still failing0 broke
Pass-rate lift
+24 pp
Tokens
+80%
Agent turns
0%
Response time
-20%
Model gemini-3.6-flashMeasured 8/16/2026v122 of 25 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 6
Prompt
I am reviewing a local points valuation JSON dataset where `_meta.last_updated` is dated 60 days ago. What operational step should be taken before using these figures for award calculations?
What was checked, without and with the skill
Checked
Without skill
With skill
Notes that dataset older than 45 days is stale due to frequent program devaluations
Missed
Passed
Instructs re-fetching source data from URLs in metadata to refresh rates
Missed
Passed
case-20 · gemini-3.6-flash · 8/16/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md104 linessingle file
Points Valuations
Reference data:data/points-valuations.json
Four sources are aggregated:
The Points Guy (TPG): optimistic, has affiliate incentive to inflate
Upgraded Points: moderate
One Mile at a Time (OMAAT): conservative
View From The Wing (VFTW): most conservative and theoretically rigorous
Each entry has:
floor — conservative minimum (use this for decision-making)
ceiling — optimistic maximum
sources — individual values from each publication
Decision Rules
Default to the floor for "should I burn points on this?" decisions. If a redemption beats the ceiling, it's genuinely exceptional. Say so.
Below the floor is objectively poor value. Flag it and suggest alternatives.
TPG systematically overvalues (affiliate incentive). VFTW and OMAAT are more useful for real decisions.
When floor and ceiling are within 0.1cpp, the value is well-established.
When floor and ceiling are 0.3cpp+ apart, mention the range and let the user decide.
The Points-vs-Cash Decision Sequence
Run these steps in order for any "should I use points?" question. Each step can end the analysis early; don't skip ahead.
Compute true cpp with the formula below — total out-of-pocket including award taxes/surcharges, not gross fare. If you don't know the surcharge yet, get it before quoting a cpp; a BA award can swing from 2.5cpp to 0.9cpp on surcharges alone.
Compare against the program's floor. Below floor → recommend cash (or a different program), and say why. At/above ceiling → call it exceptional explicitly.
Check reachability before valuing further. A great cpp in a program the user can't reach (no balance, no transfer path in data/transfer-partners.json) is not an option — drop it.
If a transfer is involved, gate through transfer-bonuses (check expiry against today's date) — an active bonus divides the effective miles cost and can flip step 2's verdict.
Check the opportunity cost of the currency, not just this redemption. UR at 1.3cpp on a flight is a loss if the user's realistic alternative is Hyatt at 1.5-2.0cpp — the benchmark for a transferable currency is its best practical use, not 1.0.
Compare against the portal quote (actual quote, not assumed rate — Points Boost is dynamic). Transfer wins on miles-count more often than portal wins on simplicity; show both numbers.
Present cpp math on both sides and a one-line verdict. User preference thresholds (e.g. a personal ~1.5cpp bar) are an overlay the user applies — still surface sub-threshold options when cash is unreasonable or points are expiring, flagged as such.
Staleness Check
Look at _meta.last_updated in the data file. If it's more than 45 days old, re-fetch from the source URLs in _meta.sources and update the file. Programs devalue regularly, and stale valuations lead to bad recommendations.
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